Improved pitch modelling for low bit-rate speech coders

During the last several years, there has been a dramatic growth of digital services, such as digital wireless and wireline communications, satellite communications and digital voice storage systems. Such services require the use of high-quality low bit-rate coders to efficiently code the speech signal before transmission or storage. The majority of such coders employ algorithms that are based on Code-Excited Linear Prediction (CELP).The goal of this thesis is to improve the quality of CELP coded speech, while keeping the basic coding format intact. The quality improvement is focused on voiced speech segments. A Pitch Pulse Averaging (PPA) algorithm has been developed to enhance the periodicity of such segments, where during steady state voicing the pitch pulse waveforms in the excitation signal evolve slowly in time. The PPA algorithm extracts a number of such pitch pulse waveforms from the past excitation, aligns them, and then averages them to produce a new pitch pulse waveform with reduced noise.The PPA algorithm has been simulated and tested on a floating point C-simulation of the G.729 8 kbps CS-ACELP coder. Objective tests verified that the algorithm contributes most during steady state voiced speech. Thus a simple voicing decision mechanism has been developed to deactivate the algorithm during unvoiced segments and voicing onsets of speech. Results verified that the algorithm has generally improved the periodicity of voiced segments by reducing the average of the weighted mean-squared error.While we were able to demonstrate improvements in objective measures, informal listening tests indicate that the already high perceptual quality of G.729 is generally not audibly altered. Nonetheless, the technique may be useful for improving the quality at lower rates, particularly for next generation low bit-rate coders operating near 4 kbps